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Generative AI in Education and Research: Opportunities, Concerns, and Solutions
Abstract
In this article, we discuss the role of generative artificial intelligence (AI) in education. The integration of AI in education has sparked a paradigm shift in teaching and learning, presenting both unparalleled opportunities and complex challenges. This paper explores critical aspects of implementing AI in education to advance educational goals, ethical considerations in scientific publications, and the attribution of credit for AI-driven discoveries. We also examine the implications of using AI-generated content in professional activities and describe equity and accessibility concerns. By weaving these key questions into a comprehensive discussion, this article aims to provide a balanced perspective on the responsible and effective use of these technologies in education, highlighting the need for a thoughtful, ethical, and inclusive approach to their integration.
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“The field also raises concerns about bias, misinformation, and the reliability of AI-generated content, particularly when used without verification in academic settings [2,20].”
From Engineering student perceptions of generative AI use in learning trust judgment and information seeking (2026) · cites this paper as [2]
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Metadata
- Authors
- Alasadi, E. A., & Baiz, C. R.
- Affiliations
- The University of Texas at Austin (US)
- Corresponding author
- Baiz, Carlos R.
- ORCID
- Baiz, Carlos R.
- Venue
- Journal of Chemical Education
- Publisher
- American Chemical Society (ACS)
- Published
- 2023-07-27
- Volume
- 100
- Issue
- 8
- Pages
- 2965-2971
- ISSN
- 0021-9584 (ISSN-L)
- 1938-1328
- OpenAlex
- W4385303098
- Cited by
- 463
- References
- 11
- Citations by year
- 2026: 113 · 2025: 183 · 2024: 154 · 2023: 13
- FWCI
- 108.66
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Journal of Chemical Education (publishedVersion)
- Funders
- Division of Chemistry (CHE-1847199)
- Welch Foundation (F-1891)
- University of Texas at Austin
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Keywords
- generative AI, artificial intelligence in education, artificial intelligence in research, authorship attribution, AI-generated content, equity and accessibility, responsible AI use, teaching-learning process
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